Dicing with the daytraders

THERE IS an old joke economists tell to mock one of the central ideas of their profession about financial markets, and as economists' jokes go it isn't bad. A professor of economics and one his students are walking down the street when they see a pounds 10 note on the pavement. The student starts to pick it up but his tutor reproaches him. "If it were really a pounds 10 bill," he says, "someone would have picked it up already."

In the same way, economists have long said there is no such thing as a free lunch, or a free pounds 10, in the stock market. Financial markets are deemed "perfect" markets, where information is readily available to everybody and is immediately priced into a stock.

From this, they deduce that prices move on the basis of irrational factors, and they move erratically in what economists call a "Random Walk". Any systematic movement would be picked up by everybody else, and they would eliminate it. Prices are not predictable with the degree of accuracy to enable anyone to make more money than the market over the long term.

The American economists Andrew Lo and Craig MacKinlay think that is wrong, and that they can prove it. Their book - A Non-Random Walk Down Wall Street (Princeton University Press) - is for economics specialists, but it has some interesting things to say about financial markets, and important messages for investors. Some of them, ironically, reinforce the basic message of the Random Walk theory: confronted with new methods of predicting the market's movements, caveat emptor.

The Random Walk theory has been a shibboleth of the economics profession for decades, reinforced by hundreds of statistical studies which seem to show it is correct, but like every shibboleth, it has its detractors and critics.

Financial professionals don't like it because it implies their work is more like witchcraft than anything else. Many investors don't much like it because it says there is no point looking for systems, trends or patterns: they are illusory, at least in the longer term.

The best-known book based on the idea, Burton Malkiel's A Random Walk Down Wall Street, has a basic message that the best way to invest is to plonk your capital in a stock index fund and let it stay there. You can't buck, or beat the market.

Messrs Lo and MacKinlay started out by testing the theory, as many have done, by examining stock market data from America for the period 1962 to 1985. What they found surprised them. Most of the publicly credited studies said this data proved market prices moved in a random way, but they found discernible patterns. In particular, it was more risky to hold a stock for a year than for a month, more than 12 times as risky. If the Random Walk theory held, the risk should simply have been the accumulation of the risk for each of the 12 months.

Their study - now widely accepted, but then very controversial - implied there werepatterns in the market's movement. "We ran into stout opposition," says Mr Lo. "But over the past few years, people have confirmed our findings." The book is only for those who are at home with the Heteroskedastic Null Hypothesis and Power Against Fractionally-Differenced Alternatives, but that is not to say it doesn't have important real-world implications.

The main lesson drawn from their research will not surprise investment professionals. "Financial markets are predictable to some degree," say Mr Lo and Mr Mackinlay in the book, and "there is a role for active management" of stocks. For most investors, the point about this theory are the strict limitations on it. We are not talking about the kinds of trend that make it possible to guess where fish will be in a river; markets are not as predictable as the weather, though they are not as random as a dice throw.

The patterns they found were not, in general, the sort of thing individual investors could use: they were discernible to large investment firms using the most sophisticated technology, and these were the firms which exploited them.

When Mr Lo and Mr MacKinlay studied data for 1986 to 1996 they found prices were more random. Part of the explanation, they believe, is that hedge funds such as D E Shaw were now using precisely the sort of patterns which they found to trade, thus smoothing out the movements. "In much the same way that innovations in biotechnology can garner superior returns for venture capitalists, innovations in financial technology can garner equally superior returns for investors," they write.

But when they looked at the period 1996 to 1998, trends started to appear again. In particular, good news was producing sharper upward spikes, and bad news was sending prices down more rapidly, before the market corrected. The market was becoming manic depressive, though against a pattern of sharply upward growth. "Short-term over-reaction seems to be much more prevalent," says Mr Lo.

The reason, he hypothesises, is the arrival of large numbers of daytraders - often financially unsophisticated people seeking a quick buck. Some trade on news from the fast-moving Internet and technology sectors; others exploit quantitative techniques to spot small but in their view significant market movements during the day. Even five years ago, it would have been hard for the individual investor to get access to the news on a real-time basis; and even harder to trade real-time to exploit it.

Yet Mr Lo continues to regard trading on the basis of these anomalies with great caution. "It's a far cry from saying that individual investors can do this," he says. "The best advice is still to read Malkiel's book."

Individuals need to be very aware of the risks that go with the rewards of trying to surf the market's anomalies on their own. "The way that investors make mistakes is not by making bad decisions, but by not knowing their own capacity for risk," he says. "The riskiness of active strategies can be very different from passive strategies, and such risks do not necessarily average out over time."

If you wanted to exploit the pattern Mr Lo and Mr Mackinlay found in the last two years, for instance, then you would take the other side of the day-traders' transactions, trading against the market in the belief that the over-reaction would correct. That carries big risks if you get the timing wrong, or if you misinterpret the market's mood. Those risks are smaller for companies which do it institutionally, though they are still present. "With sufficiently large scale, you can make money," says Mr Lo.

Investments in highly computational technology, faster information feeds and lower transaction costs will enable some people to make more money by taking higher risks. But as the world saw with the collapse of the hedge fund Long-Term Capital Management, when these things go wrong, they can go spectacularly wrong, and that was in the middle of one of the longest bull markets in history.

Investment firms can make life better for their clients by investment in technology, by making products that package risks more effectively, and by measuring and controlling transaction costs, and from that point of view, new and better investment opportunities may lie ahead, the authors say. But they are clearly deeply sceptical of the idea that success lies in a high-speed modem link, a personal computer and an online account.

The book is provocatively titled, suggesting (like a million other investment guides) the discovery of a system, but that is not so. Indeed the main conclusion seems to be that, for most of us, this brave new world of supercomputers and asymptotic distributions carries a pretty hefty downside.

"Although there are probably still only a few ways to make money reliably," say the authors, "the growing complexity of financial markets has created many ways to lose it and lose it quickly."

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